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Katerina Berková; Martina Chalupová; František Smrcka; Marek Musil; Dagmar Frendlovská – Education and Information Technologies, 2024
Learning analytics dashboards (LADs) are very important tools for contemporary education. Not only researchers, but also schools at different levels of education and students are evaluating in this way today. A large number of studies have addressed the issue, but there are few studies that have explored the possibilities of transferring the…
Descriptors: Learning Analytics, Formative Evaluation, Self Evaluation (Individuals), Universities
Flora Ji-Yoon Jin; Bhagya Maheshi; Wenhua Lai; Yuheng Li; Danijela Gasevic; Guanliang Chen; Nicola Charwat; Philip Wing Keung Chan; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Learning Analytics, 2025
This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Learning Analytics
Yuqin Yang; Yewen Chen; Xueqi Feng; Daner Sun; Shiyan Pang – Journal of Computing in Higher Education, 2024
Helping students gradually develop collective knowledge is critical but generally faces great challenges. Employing a quasi-experimental design, this study investigated the impacts and mechanisms of analytics-supported reflective assessment on the collective knowledge advancement of undergraduates. The experimental group (n = 55) engaged in…
Descriptors: Undergraduate Students, Learning Processes, Learning Analytics, Learner Engagement
Divjak, Blaženka; Svetec, Barbi; Horvat, Damir; Kadoic, Nikola – British Journal of Educational Technology, 2023
To ensure the validity of an assessment programme, it is essential to align it with the intended learning outcomes (LO). We present a model for ensuring assessment validity which supports this constructive alignment and uses learning analytics (LA). The model is based on LA that include a comparison between ideal LO weights (expressing the…
Descriptors: Test Validity, Learning Analytics, Student Centered Learning, Prerequisites
Anni Silvola; Amanda Sjöblom; Piia Näykki; Egle Gedrimiene; Hanni Muukkonen – Frontline Learning Research, 2023
An in-depth understanding of student experiences and evaluations of learning analytics dashboards (LADs) is needed to develop supportive learning analytics tools. This study investigates how students (N = 140) evaluated two student-facing LADs as a support for academic path-level self-regulated learning (SRL) through the concrete processes of…
Descriptors: Learning Analytics, Student Evaluation, Student Experience, Student Attitudes
Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Jelena Jovanovic; Andrew Zamecnik; Abhinava Barthakur; Shane Dawson – Education and Information Technologies, 2025
Higher education institutions are increasingly seeking ways to leverage the available educational data to make program and course quality improvements. The development of automated curriculum analytics can play a substantial role in this effort by bringing novel and timely insights into course and program quality. However, the adoption of…
Descriptors: Learning Analytics, Curriculum Evaluation, Evaluation Methods, Educational Objectives
Stanislav Pozdniakov; Jonathan Brazil; Mehrnoush Mohammadi; Mollie Dollinger; Shazia Sadiq; Hassan Khosravi – Journal of Learning Analytics, 2025
Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…
Descriptors: Student Evaluation, Artificial Intelligence, Student Developed Materials, Feedback (Response)
Cleon Xavier; Luiz Rodrigues; Newarney Costa; Rodrigues Neto; Gabriel Alves; Taciana Pontual Falcao; Dragan Gasevic; Rafael Ferreira Mello – IEEE Transactions on Learning Technologies, 2025
Providing timely and personalized feedback on open-ended student responses is a challenge in education due to the increased workloads and time constraints educators face. While existing research has explored how learning analytic approaches can support feedback provision, previous studies have not sufficiently investigated educators' perspectives…
Descriptors: Teacher Empowerment, Learning Analytics, Artificial Intelligence, Computer Software
Arruarte, Josu; Larrañaga, Mikel; Arruarte, Ana; Elorriaga, Jon A. – International Journal of Artificial Intelligence in Education, 2021
In order to be effective, a learning process requires the use of valid and suitable educational resources. However, measuring the quality of an educational resource is not an easy task for a teacher. The data of the performance of the students can be used to measure how appropriate the didactic resources are. Besides this data, adequate metrics…
Descriptors: Educational Resources, Educational Quality, Learning Analytics, Tests
Hector Vargas; Ruben Heradio; Gonzalo Farias; Zhongcheng Lei; Luis de la Torre – IEEE Transactions on Education, 2024
Contribution: A competency assessment framework that enables learning analytics for course monitoring and continuous improvement. Our work fills the gap in systematic methods for competency assessment in higher education. Background: Many institutions are shifting toward competency-based education (CBE), thus encouraging their educators to start…
Descriptors: Competency Based Education, Learning Analytics, Higher Education, College Students
Bo Pei; Ying Cheng; Alex Ambrose; Eva Dziadula; Wanli Xing; Jie Lu – Smart Learning Environments, 2024
The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…
Descriptors: Learning Analytics, Learning Management Systems, Computer Uses in Education, Educational Technology
Heil, Joana; Ifenthaler, Dirk – Online Learning, 2023
Online assessment is defined as a systematic method of gathering information about a learner and learning processes to draw inferences about the learner's dispositions. Online assessments provide opportunities for meaningful feedback and interactive support for learners as well as possible influences on the engagement of learners and learning…
Descriptors: Computer Assisted Testing, Higher Education, Literature Reviews, College Students
J. Keba; Vineetha K. Ramdas Nayak; N. Sajitha; S. Himiki – Advances in Physiology Education, 2024
Formative assessment is a valuable tool in medical education as it allows students to reflect on their own learning and make necessary corrections. The use of innovative techniques in formative assessment can make it more engaging and effective for students, particularly utilizing electronic tools. A word cloud is a visual representation of data…
Descriptors: Formative Evaluation, Computer Software, Student Evaluation, Physiology